Intersectionality in Housing Research: Early Reflections from a Community-based Participatory Research Partnership
Bibliographic record
Abstract
We discuss early reflections of a housing security research project focused on implementing intersectional praxis across the life cycle of community-based participatory research. Drawing on our team’s initial Co-learning Workshop, including community and academic partners, we share initial learnings of our collective engagement with the connections between intersectionality and housing security. Specifically, we reflect on three key challenges, or “hopeful hesitations,” that have emerged as we begin our collaboration: co-defining intersectionality (including both theory and implementation); integrating intersectionality into the multi-scaled complexities of housing security; and communicating the relevance of intersectionality to a wider network of actors in housing security policy and programming. We suggest that an intersectional lens is crucial to housing security work because of the ways it attends to the everyday lived experiences of housing insecurity, the interlocking forms of oppression that create differentiated experiences, and the specific contexts in which structural housing inequities take root.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.979 | 0.863 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.005 | 0.005 |
| Science and technology studies | 0.616 | 0.005 |
| Scholarly communication | 0.007 | 0.002 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.001 | 0.853 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; both teacher heads agree on what is shown here.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".